A Generic Utility Model Representing the Quality of Sensory Experience

Rainer, Benjamin; Timmerer, Christian

doi:10.1145/2648429

Cited by 8 publications

(3 citation statements)

References 15 publications

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“…Users' QoE assessment is undoubtedly time and effort demanding. However, there has been some guidance in the literature, notably the works of Rainer and Timmerer [78] and Murray et al [57]. In a nutshell, Rainer and Timmerer [78] provide the following steps in order to carry out subjective evaluations:…”

Section: Assessment and Qoe In Mulsemedia Environmentsmentioning

confidence: 99%

Mulsemedia DIY: A Survey of Devices and a Tutorial for Building Your Own Mulsemedia Environment

et al. 2019

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Multisensory experiences have been increasingly applied in Human-Computer Interaction (HCI). In recent years, it is commonplace to notice the development of haptic, olfactory, and even gustatory displays to create more immersive experiences. Companies are proposing new additions to the multisensory world and are unveiling new products that promise to offer amazing experiences exploiting mulsemedia—multiple sensorial media—where users can perceive odors, tastes, and the sensation of wind blowing against their face. Whilst researchers, practitioners and users alike are faced with a wide range of such new devices, relatively little work has been undertaken to summarize efforts and initiatives in this area. The current article addresses this shortcoming in two ways: first, by presenting a survey of devices targeting senses beyond that of sight and hearing and, second, by describing an approach to guide newcomers and experienced practitioners alike to build their own mulsemedia environment, both in a desktop setting and in an immersive 360° environment.

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Section: Assessment and Qoe In Mulsemedia Environmentsmentioning

confidence: 99%

Mulsemedia DIY: A Survey of Devices and a Tutorial for Building Your Own Mulsemedia Environment

et al. 2019

View full text Add to dashboard Cite

show abstract

“…First, how can a QoE model for HAS, which is representative of the specific, rather than aggregate, user behavior be created? Estimating QoE does not only involve application-level parameters, such as switches or freezes, but also sensorial inputs and context [79,81]. Current smartphones and tablets are already equipped with several sensors (e.g., GPS, light sensors etc.…”

Section: Personalized Qoe-centric Controlmentioning

confidence: 99%

Quality of Experience-Centric Management of Adaptive Video Streaming Services

Petrangeli

Hooft

Wauters

et al. 2018

ACM Trans. Multimedia Comput. Commun. Appl.

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Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming (HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this paper, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years.

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“…As such, research in the area of mulsemedia has focused on issues pertaining to synchronisation [1,36,46], metrics [26], cross-modal correspondences [12], and how the use of different modalities can enhance perception and sense of immersion, conveying data [39] and Virtual Reality systems [5,6,10,11,[19][20][21]28,37,38]. Given the importance of Quality of Experience (QoE) in multimedia, this concern has ported across to the mulsemedia arena, with studies focusing on assessment and modeling [13,23,35,40] as well as delivery [48].…”

Section: Introductionmentioning

confidence: 99%

When Scents Help Me Remember My Password

Alkasasbeh

Spyridonis

Ghinea

2021

ACM Trans. Appl. Percept.

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Current authentication processes overwhelmingly rely on audiovisual data, comprising images, text or audio. However, the use of olfactory data (scents) has remained unexploited in the authentication process, notwithstanding their verified potential to act as cues for information recall. Accordingly, in this paper, a new authentication process is proposed in which olfactory media are used as cues in the login phase. To this end, PassSmell , a proof of concept authentication application, is developed in which words and olfactory media act as passwords and olfactory passwords, respectively. In order to evaluate the potential of PassSmell, two different versions were developed, namely one which was olfactory-enhanced and another which did not employ olfactory media. Forty-two participants were invited to take part in the experiment, evenly split into a control and experimental group. For assessment purposes, we recorded the time taken to logon as well as the number of failed/successful login attempts; we also asked users to complete a Quality of Experience (QoE) questionnaire. In terms of time taken, a significant difference was found between the experimental and the control groups, as determined by an independent sample t-test. Similar results were found with respect to average scores and the number of successful attempts. Regarding user QoE, having olfactory media with words influenced the users positively, emphasizing the potential of using this kind of authentication application in the future.

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A Generic Utility Model Representing the Quality of Sensory Experience

Cited by 8 publications

References 15 publications

Mulsemedia DIY: A Survey of Devices and a Tutorial for Building Your Own Mulsemedia Environment

Mulsemedia DIY: A Survey of Devices and a Tutorial for Building Your Own Mulsemedia Environment

Quality of Experience-Centric Management of Adaptive Video Streaming Services

When Scents Help Me Remember My Password

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